Krista makes security software deployment elementary with IBM Watson integration

Despite the hype, automating across the software development lifecycle takes more than a splash of generative AI. Sure, generative AI can generate code, but when it comes to automating scheduling and deploying software with the security and scale that enterprises demand, leaders must ensure every step of the development lifecycle is followed.

Zimperium, a mobile-first security platform offering mobile threat defense and in-app protection, identified its deployment pain points but needed an intelligent platform to enhance its project management, messaging, and DevOps. Enter Q4 2021 HFS Hot Vendor Krista Software and its intelligent automation platform, Krista. The task Zimperium faced included maintaining hundreds of software environments with multiple releases of patches, updates, and hard fixes, with a full deployment cycle for each environment. The processes were time consuming, and each of the many human interactions introduced risk.

With NLP, teams can simply “ask” for business outcomes

Krista’s use of machine learning and IBM Watson’s natural language processing (NLP) allows Zimperium’s team to simply “ask Krista” for a particular business outcome. Krista creates IT tickets, sends messages to relevant team members, and sends reminders for any required approvals. Krista does also have its own NLP providing integrations to different NLP modules. In this instance, Krista uses Watson NLP to read the error logs and summarize the errors for the engineers. It now takes seconds for an engineer to read the exception summary versus tens of minutes to read all the logs and develop a hypothesis. Embedding Watson has also opened the way for Krista Software to work collaboratively with IBM.

By following each ticket throughout the software development life cycle (SDLC), Krista checks that each step has been adhered to, supporting the delivery of software to the right environment at the right time. With the peace of mind that comes from having a human in the loop for approvals, Zimperium can deploy software in minutes, replacing a four-hour manual process. The collaboration has already saved Zimperium $200,000, and it frees developers to develop rather than administer deployments.

With value delivered in 60 days—order-to-cash is next on the agenda

Delivered in just 60 days, the $200,000 of value Krista has already generated has made it such a hit at Zimperium that leaders have now asked Krista Software to start work on Zimperium’s order-to-cash process, and international customer support.

Krista Software isn’t resting on its laurels. It is now working even more closely with IBM to explore using watsonx—the platform HFS has called out as the first enterprise-grade offering to address the needs of the Generative Enterprise™.

The Zimperium case is a great example of AI deployment cracking a known business problem. Zimperium’s redesign of its workflow to take advantage of AI’s possibilities also shows the benefits of improving a process before automating it. As we learn to apply even smarter forms of AI, including generative AI, we look forward to seeing use cases where businesses broadly apply AI to rethink and deliver new ways of working and new sources of value.

The Bottom Line: Apply AI to known problems to get the confidence you’ll need to move on to applying generative AI

Enterprise leaders dealing with tight budgets have tough choices to make. The pressure is on to innovate—but wisely. IBM will tell you 80% of AI projects fail to make it out of the lab, but the excitement around generative AI has pushed AI to the top of many CEO agendas. In the short term, it’s smart to follow Zimperium’s path: Fix a known problem. Get some solid ROI, and then think bigger about some true value innovation.